Company Description
Version 1 has celebrated over 28 years in Technology Services and continues to be trusted by global brands to deliver solutions that drive customer success. Version 1 has several strategic technology partners including Microsoft, AWS, Oracle, Red Hat, OutSystems and Snowflake. We’re also an award-winning employer reflecting how employees are at the heart of Version 1.
We’ve been awarded: Innovation Partner of the Year Winner 2023 Oracle EMEA Partner Awards, Global Microsoft Modernising Applications Partner of the Year Award 2023, AWS Collaboration Partner of the Year - EMEA 2023 and Best Workplaces for Women by Great Place To Work in UK and Ireland 2023.
As a consultancy and service provider, Version 1 is a digital-first environment and we do things differently. We’re focused on our core values; using these we’ve seen significant growth across our practices and our Digital, Data and Cloud team is preparing for the next phase of expansion. This creates new opportunities for driven and skilled individuals to join one of the fastest-growing consultancies globally.
Job Description

EXPERIENCE & SKILLS

• Proven experience in pre-sales or client-facing architecture roles involving AI, data science, or analytics.
• Strong ability to elicit business needs and align them with AI/ML solutions in cloud environments (Azure, AWS, or GCP).
• Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search.
• Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face.
• Ability to develop architecture artefacts (e.g., HLDs), estimate effort and cost, and contribute to proposal writing.
• Strong storytelling and presentation skills; able to build confidence with senior business and technical stakeholders.
• Experience working in bid teams or alongside account executives, ideally in a consultancy or solution provider context.
• Understanding of data governance, security, and ethical AI practices.
• Ability to adapt solutions across multiple sectors (e.g., public sector, utilities, finance, health) is a strong advantage.
  Additional Information

ROLE OVERVIEW

As a Pre-Sales AI Architect, you will play a pivotal role in identifying, shaping, and securing new AI opportunities by bridging the gap between complex customer challenges and transformative, AI-powered solutions. This highly consultative role requires a strong blend of technical expertise, business acumen, and communication skills. You will work closely with clients, account teams, and delivery leads to understand customer needs, design compelling AI solutions, and contribute to successful bid strategies and proposals.
You are expected to act as a trusted advisor to both internal teams and client stakeholders, translating real-world challenges into scalable AI architectures that demonstrate tangible business value. Your work will directly support sales growth by influencing solution design, estimating effort and risk, and differentiating our offer through innovation and credibility.

KEY RESPONSIBILITIES

1. Shape AI Solutions in Response to Client Needs
   Engage with client stakeholders to uncover pain points, business drivers, and opportunities for AI-powered transformation.
   Conduct discovery workshops and assessments to define business requirements and align them with AI use cases.
2. Design and Propose AI Architectures
   Translate client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact.
   Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity.
3. Support Sales and Bid Activity
   Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture diagrams, and estimates.
   Contribute to bid strategy, win themes, and differentiators based on the latest AI technologies (e.g. GenAI, LLMs, computer vision, NLP, predictive modelling).
4. Prototype and Demonstrate
   Build proof-of-concepts (PoCs) or demos to validate solution approaches and inspire client confidence.
   Showcase AI capabilities using relevant tools (e.g. Power BI + Azure ML, Hugging Face, LangChain, GPT APIs).
5. Track Industry Trends and Use Cases
   Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across sectors.
   Advise internal stakeholders on how evolving technologies (e.g. vector databases, RAG pipelines, prompt engineering) can drive value in future proposals.
   Qualifications